Academic Profile

Academic Profile

Asst Prof Erik Cambria

Assistant Professor

School of Computer Science and Engineering
College of Engineering

Phone: (+65)6790 4328
Office: N4-02a-27

  • PhD (Computer Sci & Maths) University of Stirling 2012
  • MEng (Elect Engrg) University of Genoa 2008
  • BEng (Elect Engrg) University of Genoa 2005
Erik Cambria received his PhD in Computing Science and Mathematics in 2012 following the completion of an EPSRC project in collaboration with the MIT Media Lab, which was selected as impact case study by the University of Stirling for the UK Research Excellence Framework. After working at HP Labs India and Microsoft Research Asia, in 2014 he joined Nanyang Technological University as an assistant professor.

Dr Cambria is associate editor of several journals, e.g., NEUCOM, INFFUS, KBS, AIRE, IEEE CIM and IEEE Intelligent Systems, where he manages the Department of Affective Computing and Sentiment Analysis. He is founder of SenticNet, a spinoff offering B2B sentiment analysis services (, and is recipient of many awards, e.g., AI's 10 to Watch. Dr Cambria is involved in several international conferences as PC member, e.g., AAAI, IJCAI, UAI, ACL, and EMNLP, workshop organizer, e.g., ICDM SENTIRE, and invited speaker, e.g., IEEE SSCI 2017.
Research Interests
sentic computing
sentiment analysis
commonsense reasoning
natural language understanding
Current Projects
  • BeingTogether
  • Big Social Data Analysis
  • Brain-Inspired Natural Language Processing for the Time-Evolving Analysis of the Singaporean Blogosphere
  • Gift funds - in support of research activities
  • Human-Robot Collaborative AI for Advanced Manufacturing and Engineering (AME) Programmatic Grant : Commonsense Reasoning
  • MICE - A Multilingual Corpus of Emotion Expressions of Malay, Indonesian, Chinese and English
  • Maritime Silk Road. Past, Present and Future. A projection mapping concept design project
  • PONdER: Public Opinion of Nuclear Energy
  • Paddington
  • Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis
  • Smart Visual Analytics of Unconventional Data
  • Social Computational Analytics for Trend Discovery and Social Media Marketing
  • Twittener: Twitter speech synthesis with natural language processing
  • ‘Heritage and Innovation in digital identity design practices: the “business card” for global Internet communities'
Selected Publications
  • Y Ma, H Peng, E Cambria. (2018). Targeted aspect-based sentiment analysis via embedding commonsense knowledge into an attentive LSTM. AAAI (pp. 5876-5883).
  • E Cambria, S Poria, D Hazarika, K Kwok. (2018). SenticNet 5: Discovering conceptual primitives for sentiment analysis by means of context embeddings. AAAI (pp. 1795-1802).
  • T Young, E Cambria, I Chaturvedi, H Zhou, S Biswas, M Huang. (2018). Augmenting end-to-end dialogue systems with commonsense knowledge. AAAI (pp. 4970-4977).
  • E Cambria, S Poria, A Gelbukh, M Thelwall. (2017). Sentiment analysis is a big suitcase. IEEE Intelligent Systems, 32(6), 74-80.
  • Cambria E, Hussain A. (2015). Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis. Springer, ISBN: 978-3-319-23654-4.

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